Copyright vision : copyright jails

This article, published in ON LINE Opinion on 26 October 2006, discusses the broad ranging amendments to the Copyright Act which (in part) implement obligations under the Australia-US Free Trade Agreement (AUSFTA) which were introduced into parliament on October 19, 2006. It covers issues relating to the criminalisation of copyright infringement, user rights and liabilities, and Technological Protection Measures (TPMs).

Machine vision toolbox for MATLAB, release 3 [Software]

The Toolbox, combined with MATLAB ® and a modern workstation computer, is a useful and convenient environment for investigation of machine vision algorithms. For modest image sizes the processing rate can be sufficiently ``real-time'' to allow for closed-loop control. Focus of attention methods such as dynamic windowing (not provided) can be used to increase the processing rate. With input from a firewire or web camera (support provided) and output to a robot (not provided) it would be possible to implement a visual servo system entirely in MATLAB. Provides many functions that are useful in machine vision and vision-based control. Useful for photometry, photogrammetry, colorimetry. It includes over 100 functions spanning operations such as image file reading and writing, acquisition, display, filtering, blob, point and line feature extraction, mathematical morphology, homographies, visual Jacobians, camera calibration and color space conversion.

See-and-avoid quadcopter using fuzzy control optimized by cross-entropy

In this work we present an optimized fuzzy visual servoing system for obstacle avoidance using an unmanned aerial vehicle. The cross-entropy theory is used to optimise the gains of our controllers. The optimization process was made using the ROS-Gazebo 3D simulation with purposeful extensions developed for our experiments. Visual servoing is achieved through an image processing front-end that uses the Camshift algorithm to detect and track objects in the scene. Experimental flight trials using a small quadrotor were performed to validate the parameters estimated from simulation. The integration of cross- entropy methods is a straightforward way to estimate optimal gains achieving excellent results when tested in real flights.

Field-of-view, detection range, and false alarm trade-offs in vision-based aircraft detection

This paper presents a survey of previously presented vision based aircraft detection flight test, and then presents new flight test results examining the impact of camera field-of view choice on the detection range and false alarm rate characteristics of a vision-based aircraft detection technique. Using data collected from approaching aircraft, we examine the impact of camera fieldof-view choice and confirm that, when aiming for similar levels of detection confidence, an improvement in detection range can be obtained by choosing a smaller effective field-of-view (in terms of degrees per pixel).

See and avoid using on-board computer vision

The integration of unmanned aircraft into civil airspace is a complex issue. One key question is whether unmanned aircraft can operate just as safely as their manned counterparts. The absence of a human pilot in unmanned aircraft automatically points to a deficiency that is the lack of an inherent see-and-avoid capability. To date, regulators have mandated that an “equivalent level of safety” be demonstrated before UAVs are permitted to routinely operate in civil airspace. This chapter proposes techniques, methods, and hardware integrations that describe a “sense-and-avoid” system designed to address the lack of a see-and-avoid capability in UAVs.

Development of a 3D culture system to study the skeletal metastasis of prostate cancer

In the cancer research field, most in vitro studies still rely on two-dimensional (2D) cultures. However, the trend is rapidly shifting towards using a three-dimensional (3D) culture system. This is because 3D models better recapitulate the microenvironment of cells, and therefore, yield cellular and molecular responses that more accurately describe the pathophysiology of cancer. By adopting technology platforms established by the tissue engineering discipline, it is now possible to grow cancer cells in extracellular matrix (ECM)-like environments and dictate the biophysical and biochemical properties of the matrix. In addition, 3D models can be modified to recapitulate different stages of cancer progression for instance from the initial development of tumor to metastasis. Inevitably, to recapitulate a heterotypic condition, comprising more than one cell type, it requires a more complex 3D model. To date, 3D models that are available for studying the prostate cancer (CaP)-bone interactions are still lacking. Therefore, the aim of this study is to establish a co-culture model that allows investigation of direct and indirect CaP-bone interactions. Prior to that, 3D polyethylene glycol (PEG)-based hydrogel cultures for CaP cells were first developed and growth conditions were optimised. Characterization of the 3D hydrogel cultures show that LNCaP cells form a multicellular mass that resembles avascular tumor. In comparison to 2D cultures, besides the difference in cell morphology, the response of LNCaP cells to the androgen analogue (R1881) stimulation is different compared to the cells in 2D cultures. This discrepancy between 2D and 3D cultures is likely associated with the cell-cell contact, density and ligand-receptor interactions. Following the 3D monoculture study, a 3D direct co-culture model of CaP cells and the human tissue engineered bone (hTEBC) construct was developed. Interactions between the CaP cells and human osteoblasts (hOBs) resulted in elevation of Matrix Metalloproteinase 9 (MMP9) for PC-3 cells and Prostate Specific Antigen (PSA) for LNCaP cells. To further investigate the paracrine interaction of CaP cells and (hOBs), a 3D indirect co-culture model was developed, where LNCaP cells embedded within PEG hydrogels were co-cultured with hTEBC. It was found that the cellular changes observed reflect the early event of CaP colonizing the bone site. In the absence of androgens, interestingly, up-regulation of PSA and other kallikreins is also detected in the co-culture compared to the LNCaP monoculture. This non androgenic stimulation could be triggered by the soluble factors secreted by the hOB such as Interleukin-6. There are also decrease in alkaline phosphatase (ALP) activity and down-regulation of genes of the hOB when co-cultured with LNCaP cells that have not been previously described. These genes include transforming growth factor β1 (TGFβ1), osteocalcin and Vimentin. However, no changes to epithelial markers (e.g E-cadherin, Cytokeratin 8) were observed in both cell types from the co-culture. Some of these intriguing changes observed in the co-cultures that had not been previously described have enriched the basic knowledge of the CaP cell-bone interaction. From this study, we have shown evidence of the feasibility and versatility of our established 3D models. These models can be adapted to test various hypotheses for studies pertaining to underlying mechanisms of bone metastasis and could provide a vehicle for anticancer drug screening purposes in the future.

3D-printing of highly uniform CaSiO3 ceramic scaffolds : preparation, characterization and in vivo osteogenesis

Calcium silicate (CaSiO3, CS) ceramics have received significant attention for application in bone regeneration due to their excellent in vitro apatite-mineralization ability; however, how to prepare porous CS scaffolds with a controllable pore structure for bone tissue engineering still remains a challenge. Conventional methods could not efficiently control the pore structure and mechanical strength of CS scaffolds, resulting in unstable in vivo osteogenesis. The aim of this study is to set out to solve these problems by applying a modified 3D-printing method to prepare highly uniform CS scaffolds with controllable pore structure and improved mechanical strength. The in vivo osteogenesis of the prepared 3D-printed CS scaffolds was further investigated by implanting them in the femur defects of rats. The results show that the CS scaffolds prepared by the modified 3D-printing method have uniform scaffold morphology. The pore size and pore structure of CS scaffolds can be efficiently adjusted. The compressive strength of 3D-printed CS scaffolds is around 120 times that of conventional polyurethane templated CS scaffolds. 3D-Printed CS scaffolds possess excellent apatite-mineralization ability in simulated body fluids. Micro-CT analysis has shown that 3D-printed CS scaffolds play an important role in assisting the regeneration of bone defects in vivo. The healing level of bone defects implanted by 3D-printed CS scaffolds is obviously higher than that of 3D-printed b-tricalcium phosphate (b-TCP) scaffolds at both 4 and 8 weeks. Hematoxylin and eosin (H&E) staining shows that 3D-printed CS scaffolds induce higher quality of the newly formed bone than 3D-printed b-TCP scaffolds. Immunohistochemical analyses have further shown that stronger expression of human type I collagen (COL1) and alkaline phosphate (ALP) in the bone matrix occurs in the 3D-printed CS scaffolds than in the 3D-printed b-TCP scaffolds. Considering these important advantages, such as controllable structure architecture, significant improvement in mechanical strength, excellent in vivo osteogenesis and since there is no need for second-time sintering, it is indicated that the prepared 3D-printed CS scaffolds are a promising material for application in bone regeneration.

HMM triangle relative entropy concepts in sequential change detection applied to vision-based dim target manoeuvre detection

The quick detection of abrupt (unknown) parameter changes in an observed hidden Markov model (HMM) is important in several applications. Motivated by the recent application of relative entropy concepts in the robust sequential change detection problem (and the related model selection problem), this paper proposes a sequential unknown change detection algorithm based on a relative entropy based HMM parameter estimator. Our proposed approach is able to overcome the lack of knowledge of post-change parameters, and is illustrated to have similar performance to the popular cumulative sum (CUSUM) algorithm (which requires knowledge of the post-change parameter values) when examined, on both simulated and real data, in a vision-based aircraft manoeuvre detection problem.

Enterprise systems curricula for Asia-Pacific region : a vision for 2020

Enterprise Systems (ES) have emerged as possibly the most important and challenging development in the corporate use of information technology in the last decade. Organizations have invested heavily in these large, integrated application software suites expecting improvments in; business processes, management of expenditure, customer service, and more generally, competitiveness, improved access to better information/knowledge (i.e., business intelligence and analytics). Forrester survey data consistently shows that investment in ES and enterprise applications in general remains the top IT spending priority, with the ES market estimated at $38 billion and predicted to grow at a steady rate of 6.9%, reaching $50 billion by 2012 (Wang & Hamerman, 2008). Yet, organizations have failed to realize all the anticipated benefits. One of the key reasons is the inability of employees to properly utilize the capabilities of the enterprise systems to complete the work and extract information critical to decision making. In response, universities (tertiary institutes) have developed academic programs aimed at addressing the skill gaps. In parallel with the proliferation of ES, there has been growing recognition of the importance of Teaching Enterprise Systems at tertiary education institutes. Many academic papers have discused the important role of Enterprise System curricula at tertiary education institutes (Ask, 2008; Hawking, 2004; Stewart, 2001), where the teaching philosophises, teaching approaches and challenges in Enterprise Systems education were discussed. Following the global trends, tertiary institutes in the Pacific-Asian region commenced introducing Enterprise System curricula in late 1990s with a range of subjects (a subject represents a single unit, rather than a collection of units; which we refer to as a course) in faculties / schools / departments of Information Technology, Business and in some cases in Engineering. Many tertiary educations commenced their initial subject offers around four salient concepts of Enterprise Systems: (1) Enterprise Systems implementations, (2) Introductions to core modules of Enterprise Systems, (3) Application customization using a programming language (e.g. ABAP) and (4) Systems Administration. While universities have come a long way in developing curricula in the enterprise system area, many obstacles remain: high cost of technology, qualified faculty to teach, lack of teaching materials, etc.

Lost in translation (and rotation) : rapid extrinsic calibration for 2D and 3D LIDARs

This paper describes a novel method for determining the extrinsic calibration parameters between 2D and 3D LIDAR sensors with respect to a vehicle base frame. To recover the calibration parameters we attempt to optimize the quality of a 3D point cloud produced by the vehicle as it traverses an unknown, unmodified environment. The point cloud quality metric is derived from Rényi Quadratic Entropy and quantifies the compactness of the point distribution using only a single tuning parameter. We also present a fast approximate method to reduce the computational requirements of the entropy evaluation, allowing unsupervised calibration in vast environments with millions of points. The algorithm is analyzed using real world data gathered in many locations, showing robust calibration performance and substantial speed improvements from the approximations.

Integrated vision-based attitude estimation

For many years, computer vision has lured researchers with promises of a low-cost, passive, lightweight and information-rich sensor suitable for navigation purposes. The prime difficulty in vision-based navigation is that the navigation solution will continually drift with time unless external information is available, whether it be cues from the appearance of the scene, a map of features (whether built online or known a priori), or from an externally-referenced sensor. It is not merely position that is of interest in the navigation problem. Attitude (i.e. the angular orientation of a body with respect to a reference frame) is integral to a visionbased navigation solution and is often of interest in its own right (e.g. flight control). This thesis examines vision-based attitude estimation in an aerospace environment, and two methods are proposed for constraining drift in the attitude solution; one through a novel integration of optical flow and the detection of the sky horizon, and the other through a loosely-coupled integration of Visual Odometry and GPS position measurements. In the first method, roll angle, pitch angle and the three aircraft body rates are recovered though a novel method of tracking the horizon over time and integrating the horizonderived attitude information with optical flow. An image processing front-end is used to select several candidate lines in a image that may or may not correspond to the true horizon, and the optical flow is calculated for each candidate line. Using an Extended Kalman Filter (EKF), the previously estimated aircraft state is propagated using a motion model and a candidate horizon line is associated using a statistical test based on the optical flow measurements and location of the horizon in the image. Once associated, the selected horizon line, along with the associated optical flow, is used as a measurement to the EKF. To evaluate the accuracy of the algorithm, two flights were conducted, one using a highly dynamic Uninhabited Airborne Vehicle (UAV) in clear flight conditions and the other in a human-piloted Cessna 172 in conditions where the horizon was partially obscured by terrain, haze and smoke. The UAV flight resulted in pitch and roll error standard deviations of 0.42° and 0.71° respectively when compared with a truth attitude source. The Cessna 172 flight resulted in pitch and roll error standard deviations of 1.79° and 1.75° respectively. In the second method for estimating attitude, a novel integrated GPS/Visual Odometry (GPS/VO) navigation filter is proposed, using a structure similar to a classic looselycoupled GPS/INS error-state navigation filter. Under such an arrangement, the error dynamics of the system are derived and a Kalman Filter is developed for estimating the errors in position and attitude. Through similar analysis to the GPS/INS problem, it is shown that the proposed filter is capable of recovering the complete attitude (i.e. pitch, roll and yaw) of the platform when subjected to acceleration not parallel to velocity for both the monocular and stereo variants of the filter. Furthermore, it is shown that under general straight line motion (e.g. constant velocity), only the component of attitude in the direction of motion is unobservable. Numerical simulations are performed to demonstrate the observability properties of the GPS/VO filter in both the monocular and stereo camera configurations. Furthermore, the proposed filter is tested on imagery collected using a Cessna 172 to demonstrate the observability properties on real-world data. The proposed GPS/VO filter does not require additional restrictions or assumptions such as platform-specific dynamics, map-matching, feature-tracking, visual loop-closing, gravity vector or additional sensors such as an IMU or magnetic compass. Since no platformspecific dynamics are required, the proposed filter is not limited to the aerospace domain and has the potential to be deployed in other platforms such as ground robots or mobile phones.